Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence
Estimation of rainfall intensity–duration thresholds, used for the identification of debris flow/landslide triggering rainfall events, has been traditionally based on raingauge observations. The main drawback of using information from gauges is that the measurement stations are usually located far a...
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Published in | Geomorphology (Amsterdam, Netherlands) Vol. 221; pp. 286 - 297 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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Amsterdam
Elsevier B.V
15.09.2014
Elsevier |
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Abstract | Estimation of rainfall intensity–duration thresholds, used for the identification of debris flow/landslide triggering rainfall events, has been traditionally based on raingauge observations. The main drawback of using information from gauges is that the measurement stations are usually located far away from the debris flow initiation areas. In complex terrain where debris flows take place, the spatial variability of rainfall can be very high and this translates in large uncertainty of raingauge-based estimates of debris flow triggering rainfall. This work focuses on the assessment of the impact of rainfall estimation uncertainty on identification and use of rainfall thresholds for debris flow occurrence. The Upper Adige River basin, Northern Italy, is the area of study. A detailed database of more than 400 identified debris flow initiation points during the period 2000–2010 and a raingauge network of 100 stations comprise the database used for this work. The methodology examines the intensity–duration thresholds derived from a set of raingauges that are assumed to be located at debris flow initiation points (DFRs) and an equivalent set of raingauges assumed to have the role of the closest (to debris flow) available measurement (MRs). A set of reference rainfall thresholds is used to identify the rainfall events at DFRs that “triggered” debris flows (i.e. exceed the threshold). For these same events, the corresponding rainfall thresholds are derived from MR observations. Comparison between the rainfall thresholds derived from DFRs and MRs revealed that uncertainty in rainfall estimation has a major impact on estimated intensity–duration thresholds. Specifically, the results showed that thresholds estimated from MR observations are consistently underestimated. Evaluation of the estimated thresholds for warning procedures showed that while detection is high, the main issue is the high false alarm ratio, which limits the overall accuracy of the procedure. Overall performance on debris flow prediction was shown to be good for low rainfall thresholds and poor for high rainfall thresholds examined. Lastly, it was found that filtering out rainfall events with duration <12h may improve bias in estimated thresholds and performance for high rainfall thresholds.
•Rainfall estimation uncertainty affects identification of debris flow thresholds.•Rainfall uncertainty leads to large underestimation of the threshold parameters.•The use of a biased threshold strongly limits the accuracy of warnings. |
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AbstractList | Estimation of rainfall intensity–duration thresholds, used for the identification of debris flow/landslide triggering rainfall events, has been traditionally based on raingauge observations. The main drawback of using information from gauges is that the measurement stations are usually located far away from the debris flow initiation areas. In complex terrain where debris flows take place, the spatial variability of rainfall can be very high and this translates in large uncertainty of raingauge-based estimates of debris flow triggering rainfall. This work focuses on the assessment of the impact of rainfall estimation uncertainty on identification and use of rainfall thresholds for debris flow occurrence. The Upper Adige River basin, Northern Italy, is the area of study. A detailed database of more than 400 identified debris flow initiation points during the period 2000–2010 and a raingauge network of 100 stations comprise the database used for this work. The methodology examines the intensity–duration thresholds derived from a set of raingauges that are assumed to be located at debris flow initiation points (DFRs) and an equivalent set of raingauges assumed to have the role of the closest (to debris flow) available measurement (MRs). A set of reference rainfall thresholds is used to identify the rainfall events at DFRs that “triggered” debris flows (i.e. exceed the threshold). For these same events, the corresponding rainfall thresholds are derived from MR observations. Comparison between the rainfall thresholds derived from DFRs and MRs revealed that uncertainty in rainfall estimation has a major impact on estimated intensity–duration thresholds. Specifically, the results showed that thresholds estimated from MR observations are consistently underestimated. Evaluation of the estimated thresholds for warning procedures showed that while detection is high, the main issue is the high false alarm ratio, which limits the overall accuracy of the procedure. Overall performance on debris flow prediction was shown to be good for low rainfall thresholds and poor for high rainfall thresholds examined. Lastly, it was found that filtering out rainfall events with duration <12h may improve bias in estimated thresholds and performance for high rainfall thresholds.
•Rainfall estimation uncertainty affects identification of debris flow thresholds.•Rainfall uncertainty leads to large underestimation of the threshold parameters.•The use of a biased threshold strongly limits the accuracy of warnings. Estimation of rainfall intensity-duration thresholds, used for the identification of debris flow/landslide triggering rainfall events, has been traditionally based on raingauge observations. The main drawback of using information from gauges is that the measurement stations are usually located far away from the debris flow initiation areas. In complex terrain where debris flows take place, the spatial variability of rainfall can be very high and this translates in large uncertainty of raingauge-based estimates of debris flow triggering rainfall. This work focuses on the assessment of the impact of rainfall estimation uncertainty on identification and use of rainfall thresholds for debris flow occurrence. The Upper Adige River basin, Northern Italy, is the area of study. A detailed database of more than 400 identified debris flow initiation points during the period 2000-2010 and a raingauge network of 100 stations comprise the database used for this work. The methodology examines the intensity-duration thresholds derived from a set of raingauges that are assumed to be located at debris flow initiation points (DFRs) and an equivalent set of raingauges assumed to have the role of the closest (to debris flow) available measurement (MRs). A set of reference rainfall thresholds is used to identify the rainfall events at DFRs that "triggered" debris flows (i.e. exceed the threshold). For these same events, the corresponding rainfall thresholds are derived from MR observations. Comparison between the rainfall thresholds derived from DFRs and MRs revealed that uncertainty in rainfall estimation has a major impact on estimated intensity-duration thresholds. Specifically, the results showed that thresholds estimated from MR observations are consistently underestimated. Evaluation of the estimated thresholds for warning procedures showed that while detection is high, the main issue is the high false alarm ratio, which limits the overall accuracy of the procedure. Overall performance on debris flow prediction was shown to be good for low rainfall thresholds and poor for high rainfall thresholds examined. Lastly, it was found that filtering out rainfall events with duration <12h may improve bias in estimated thresholds and performance for high rainfall thresholds. |
Author | Guzzetti, Fausto Nikolopoulos, Efthymios I. Borga, Marco Crema, Stefano Marchi, Lorenzo Marra, Francesco |
Author_xml | – sequence: 1 givenname: Efthymios I. orcidid: 0000-0002-5206-1249 surname: Nikolopoulos fullname: Nikolopoulos, Efthymios I. email: efthymios.nikolopoulos@unipd.it organization: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy – sequence: 2 givenname: Stefano surname: Crema fullname: Crema, Stefano organization: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy – sequence: 3 givenname: Lorenzo surname: Marchi fullname: Marchi, Lorenzo organization: National Research Council, IRPI, Padova, Italy – sequence: 4 givenname: Francesco surname: Marra fullname: Marra, Francesco organization: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy – sequence: 5 givenname: Fausto surname: Guzzetti fullname: Guzzetti, Fausto organization: National Research Council, IRPI, Perugia, Italy – sequence: 6 givenname: Marco surname: Borga fullname: Borga, Marco organization: Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy |
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Keywords | Debris flow Raingauge network design Rainfall estimation Precipitation threshold rivers detection rainfall atmospheric precipitation debris flows accuracy rain water landslides prediction data bases filtering landform evolution |
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SubjectTerms | Assessments Debris Debris flow Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Exact sciences and technology Filtering Freshwater Geomorphology, landform evolution Italy landscapes landslides Marine and continental quaternary Natural hazards: prediction, damages, etc Precipitation threshold prediction rain rain gauges Rainfall Rainfall estimation Raingauge network design Stations Surficial geology Thresholds Uncertainty watersheds |
Title | Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence |
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